AI models are becoming more capable, but exactly what business adoption will look like remains a big question. In an effort to shape that future, labs like Anthropic and OpenAI have created separate businesses dedicated to deploying AI engineers in their clients’ offices — a bet that helping businesses figure out how to use their AI models is the next trillion-dollar category.
One of those businesses now has a name: Ode with Anthropic is the $1.5 billion AI implementation company that the AI Lab launched in May as part of a joint venture with Blackstone, Hellman & Friedman, Goldman Sachs and others. The move follows OpenAI’s take on it, The Deployment Company, underscoring the growing recognition among frontier AI labs that winning business customers requires much more than shipping better models.
Ode was originally conceived by Blackstone, which noticed a gap when it had enlisted large consulting firms and small AI service boutiques to implement AI across its portfolio companies. One of those boutiques, artificial intelligence services startup Fractional AI, apparently stood out, and the consortium acquired the startup shortly after its announcement. (Fractional ended an 11-month partnership with OpenAI when it was acquired.)
Fractional has become the foundation of what is now Ode – a sort of “scaled boutique” AI services company. And its leaders have ambitious goals.
“It’s very easy to envision this as a trillion dollar company someday if we execute well,” Chris Taylor, CEO of Ode and co-founder of Fractional, told TechCrunch in an exclusive interview. “The key business challenge is how do you get through this phase of overgrowth without losing focus on quality?”
Ode currently employs 100 engineers and works closely with Anthropic’s applied AI team to identify where technology can have an impact on different businesses and build systems tailored to each organization’s operations.
Anthropic’s internal team will continue to focus on strategic, mission-aligned deployments, a spokesperson told TechCrunch. The private equity firms backing Ode will pitch their own portfolio companies to the consortium as potential clients, although Ode will not limit sales of its services to those companies.
For Ode, an ideal customer is one whose CEO delivers on the promise, according to Taylor.
“A lot of the work we do is the top priority or two for the CEO of the company,” Taylor said. “It’s the most important product feature the company is going to build over the next two years, or iterates the most important business process it has.”
Ode will operate on a “Claude-first” principle, meaning it will implement Anthropic’s technology, including features like the Claude Tag in Slack, whenever possible. However, the company is not limited to Anthropic’s technology and will use competing AI products if necessary.
Eddie Siegel, chief technologist at Ode and co-founder of Fractional, says the venture’s secret sauce is its quality of implementation and ability to create custom solutions for business problems.
“I think model choice matters, but it’s not where the majority of calories are spent,” Siegel said. “It’s a component in a system that needs to be built. It’s like choosing a programming language when you’re building a software […] I wouldn’t define an enterprise transformation in terms of whether they choose Python or Java.”
Taylor added that the founding belief behind Ode is that “non-AI companies will be among the big winners of this whole AI moment if they adopt the technology the right way.” But taking AI, “that magical, hallucinogenic ingredient” and reconnecting core business processes or customer experiences with it requires a lot of help, he said.
“This requires top-caliber applied AI talent, which is not something most companies have,” Taylor said.
Ode executives describe their team as elite generalist software engineers, more than half of whom are former founders—the kind of people who can “take a really hard technical problem, but also own something end-to-end,” according to Siegel. Or as one Blackstone executive put it: a group of “senior” engineers, the “special forces,” not an army of forward-deployed engineers (FDEs).
As several people involved in the venture told TechCrunch, demand for such FDE teams far outstrips supply. Ode’s goal is to continue to scale internationally as well, while maintaining its firm position in the boutique — in other words, running continuous assessments to measure the business impact of AI applications.
But in a world where top engineering talent is already scarce, maintaining and growing such a team is a real challenge. If becoming an elite applied AI engineer requires experience as an entrepreneur, systems-first thinking, AI tricks, and enterprise product judgment, could Ode train enough people to meet the demand?
Combine these difficulties with the fact that Ode will be competing not only with OpenAI’s The Deployment Company, but also with consulting giants such as Deloitte and Accenturewhich have created their own FDE groups.
Siegel isn’t too worried about the shrinking pool of big general engineers.
“It’s never been an easier time to be an entrepreneur,” he said. “You learn so much trying to own end-to-end problems, trying to achieve product-market fit, moving the needle on a business. There’s a lot you learn there that you don’t just learn from solving a narrow problem. That’s the skill set that fits well with Ode.”
Whether enough of these mechanics will emerge remains an open question. But if Ode and its backers are right, the next big AI race won’t just be about the best models, but who can successfully put those models to work at the world’s biggest companies.
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